Enterprise Consulting

Alumni Network

FAQ

We have a lot of master students in Data Scientist program with different academic backgrounds. They got very good position as ‘Data Scientist’ or ‘Data Analyst’ after they graduate from our program. ‘Phd’ is not a requirement to apply for this 20 weeks training.

In general, if you are a students in CS/EE, we will suggest you to consider ‘Data Engineer’ track first, because Data Engineer requires more programming skills. But you are welcome to join the ‘Data Scientist’ track too. For the ‘Data Scientist’ track, we have real diversity in academic background. You will find students with major in Chemical Engineer, Mechanical Engineer, Environmental Engineer, Statistics, Math, Finance, Economics, Physics, and etc.

Programming is an important part of our training package. However, we will start easy, and provide more courses like python/java programming to help you get used to it.

You will get intensive training in python/java programming in the Data Scientist/Data Engineer track. In addition to big data tools, you’ll learn techniques and fundamental concepts from industry experts. Our aim is to lead you learn how to excavate value from big data and leverage it. Besides, we have a 10-week internship or end to end project to help you get hands-on experience.

The free/cheap online courses are not practical. They teach the entry-level knowledge of data engineer/scientist. While everyone can take it and pass it easily, how could you stand out among your competitors?

In Data Application Lab, we provide real project or even internship opportunities for you to get hands-on experience. This project is not the ‘capstone’ project which can be done in 2 weeks. We will give you 10 weeks, under the guidance of our TA and Instructors, to complete the End-to-End project. This project is ‘high-profile’ that it can be used as your Demo for interview. You won’t use college courses’ project for your job interview, will you?

You can learn knowledge from both Coursera as well as from us. However, if your goal is to find a job, only we can help.

No, no, no. This is the biggest misunderstanding for the ‘self-taught’ data scientist amateurs.

Data scientist usually have to spend 80% of their time doing data cleaning, data ETL. Machine Learning is only the last part of the stream-line in data application development in real companies.

In our program, we will cover topics like machine learning, but also other necessary topics like data ETL in Hadoop ecosystem, Spark machine learning, and guide you through the real ‘End2End’ project. You will then know that, data scientist is way beyond Machine Learning

‘Lambda’ data architecture is the vastest used data architecture in Silicon Valley for real-time streaming. Whether you can build a data application based on ‘Lambda’ architecture, is a criterion to differentiate ‘ready to use’ Data Engineer from ‘book-collector’ Data Engineer.

The Data Engineer program is very practical. We focus on real-time data streaming in Hadoop and Spark, which is also the real need from companies in all industry. You can learn knowledge from both Coursera as well as from us. However, if your goal is to find a job, only we can help.